Linking the length scales | Nature Machine Intelligence

Linking the length scales | Nature Machine Intelligence

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A challenge for multiscale simulations is how to link the macroscopic and microscopic length scales effectively. A new machine-learning-based sampling approach enables full exploration of


macro configurations while retaining the precision of a microscale model. Access through your institution Buy or subscribe This is a preview of subscription content, access via your


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institutional subscriptions * Read our FAQs * Contact customer support REFERENCES * Bhatia, H. et al. _Nat. Mach. Intell_. https://doi.org/10.1038/s42256-021-00327-w (2021). * Karr, J. R. et


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AFFILIATIONS * IBM Almaden Research Center, San Jose, CA, USA Shangying Wang & Simone Bianco * Center for Cellular Construction, San Francisco, CA, USA Shangying Wang & Simone Bianco


Authors * Shangying Wang View author publications You can also search for this author inPubMed Google Scholar * Simone Bianco View author publications You can also search for this author


inPubMed Google Scholar CORRESPONDING AUTHOR Correspondence to Shangying Wang. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. RIGHTS AND PERMISSIONS


Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wang, S., Bianco, S. Linking the length scales. _Nat Mach Intell_ 3, 374–375 (2021). https://doi.org/10.1038/s42256-021-00351-w


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